Road network perception system based on edge calculation

Abstract

The utility model relates to the field of traffic safety control, and particularly discloses a road network sensing system based on edge computing, which comprises a cloud platform, a response terminal, an edge computing controller, an industrial personal computer, a communication module, a power supply module, an RSU unit and a vehicle-mounted OBU unit, the RSU unit is installed on the side of a road of a congested road section, and the vehicle-mounted OBU unit is installed on each vehicle. The edge computing controller is in data communication with the cloud platform through the communication module, the edge computing controller collects vehicle data of the RSU unit and processes the vehicle data, and a vehicle data processing result is transmitted to the cloud platform and transmitted to the industrial personal computer at the same time; the industrial personal computer controls the response terminals in the coverage area of the industrial personal computer to execute actions according to instructions of the edge computing controller; the response terminal is installed on the road side of a congested road and / or installed on a ramp or a tunnel or a road side of the front section of the congested road. According to the scheme, the problem that a vehicle owner behind cannot timely know the congestion condition of a road through equipment on a road network in time when the traffic congestion occurs on the road at present can be solved.

Description

TECHNICAL FIELD

[0001] The utility model relates to the field of traffic safety control, concretely relates to a road network sensing system based on edge computing. BACKGROUND

[0002] If an occasional highway or bypass highway traffic jam event cannot be timely informed, the number of vehicles will continue to increase, and when the congestion occurs in the middle of a long straight road section, there is no ramp or branch road to turn around, which will eventually cause extensive traffic congestion, and in severe cases, some road sections may completely lose their traffic capacity. At the same time, this large-scale traffic congestion will further hinder rescue vehicles from reaching the scene quickly after an accident, thereby delaying the rescue process.

[0003] The prior art such as Chinese patent No. CN110021182B provides a road congestion information prompting method and system, which includes: acquiring the picture of the congestion section and generating congestion prompt information; the user requests to acquire the congestion prompt information, and judges to continue to proceed or to detour according to the congestion prompt information; the network cloud receives the picture of the congestion section taken by the user driving on the congestion section and calculates the time interval between the picture of the congestion section taken by the user driving on the congestion section and the picture of the congestion section taken by the user driving on the congestion section received by the network cloud.

[0004] The defect of the above-mentioned scheme is that the image information collected by the camera needs to be sent to the cloud server for processing, which results in the need for long-term operation of image processing tasks. With the large increase in Internet of Things devices, the amount of data processing is becoming larger and larger, the network transmission pressure is also becoming larger and larger, the long-term cost of the cloud server may increase, and when a large amount of image information needs to be processed, bidirectional transmission is required, which is time-consuming and occupies bandwidth. Network delay may cause the processing speed to slow down, especially when remotely accessing the cloud server, network delay will cause the road congestion information to be unable to be conveyed to the subsequent vehicle owner in time. Moreover, when notifying the vehicle owner, the APP software pre-installed on the vehicle owner's terminal is used, such as navigation software. If the vehicle owner does not use the APP software for road navigation, and the road network equipment on both sides of the road or the road does not timely send congestion prompt information, the vehicle owner may not be able to timely learn about the congestion situation of the road ahead, thereby failing to timely avoid the risk of traffic jam. Therefore, our company proposes a road network sensing system based on edge computing to solve the above-mentioned problems. UTILITY MODEL CONTENTS

[0005] The utility model provides a road network sensing system based on edge computing, which solves the problem that the vehicle owner behind cannot timely learn about the congestion situation of the road through the equipment on the road network when traffic congestion occurs on the road.

[0006] The utility model discloses a technical scheme as follows to solve the above-mentioned problems: a road network sensing system based on edge computing, comprising a cloud platform, a response terminal, an edge computing controller, an industrial computer, a communication module, a power supply module, an RSU unit and a vehicle-mounted OBU unit, the RSU unit is installed on the side of the road of a congested road section, the vehicle-mounted OBU unit is installed on each vehicle, the edge computing controller communicates data with the cloud platform through the communication module, the edge computing controller collects vehicle data of the RSU unit and processes the vehicle data, the vehicle data processing result is transmitted to the cloud platform and the industrial computer at the same time, the industrial computer controls the response terminal in its coverage range to execute actions according to the instruction of the edge computing controller; the response terminal is installed on the roadside of a congested road and / or installed on the ramp or tunnel or roadside of the front section of a congested road.

[0007] The basic principle of the scheme is that the vehicle-mounted OBU units on different vehicles and the roadside RSU units arranged on the side of the road perform road condition collection work, when the vehicle approaches the roadside RSU unit, the vehicle-mounted OBU unit and the roadside RSU unit are connected through dedicated short-range communication, the roadside RSU unit collects all vehicle-mounted OBU units in the passing range at regular intervals, compares the vehicle identity information ID of the OBU unit and the RSSI value (signal strength) when communicating with each vehicle-mounted OBU unit, judges the congestion state according to the number of vehicles and the RSSI value change of each vehicle-mounted OBU unit, the method for judging road congestion is prior art, the RSU unit sends the congestion vehicle data to the edge computing controller, the edge computing controller transmits to the cloud platform and the industrial computer in its coverage range after receiving, opens the response device through the industrial computer, thereby reminding the newly entered vehicle on the congested road, reminding the vehicle about to enter the congested road at the ramp, reminding the vehicle in the tunnel in the front section of the congested road.

[0008] The beneficial effects of the scheme are that, since road congestion is occasional, when the driver does not use the APP software but relies on his own memory to drive when the road is congested, the vehicle owner cannot timely obtain the road congestion situation, and cannot timely adjust his driving route, the scheme sets different response devices in the front section of the congested road, even if the driver does not use the APP, he can also timely obtain the road congestion information, which can help the driver to timely adjust the vehicle speed and driving route.

[0009] Further, the response terminal comprises a high-speed warning board, the high-speed warning board is erected on the ramp in the front section of the congested road, and the high-speed warning board can display the information of the congested road section direction and congestion time.

[0010] Further, the response terminal comprises a tunnel warning board and a plurality of indicator lights, the tunnel warning board and the indicator lights are installed in the tunnel in front of the congested road section, the tunnel warning board can display information of the congested road section direction and congestion time, and the indicator lights are installed on the inner wall of the tunnel in the circumferential direction.

[0011] Further, the response terminal comprises an alarm horn and a signal light, the signal light is installed on the roadside of the congested road, the alarm horn is installed at the top end of the signal light, and the alarm horn can play voice broadcast for warning.

[0012] Further, the edge computing controller comprises an embedded processor, and the embedded processor is externally provided with a USB interface and an RS485 interface.

[0013] Further, the embedded processor is an ARM Cortex-A7 processor, and the embedded processor is externally connected with an extended memory. BRIEF DESCRIPTION OF DRAWINGS

[0014] Figure 1 is a structural block diagram of the embodiment of the utility model;

[0015] Figure 2 is a schematic view of the embodiment of the utility model located on the side of the crowded road;

[0016] Figure 3 is a schematic view of the embodiment of the utility model located in the tunnel;

[0017] Figure 4 is a schematic view of the ramp in front of the crowded road in the embodiment of the utility model. DETAILED DESCRIPTION

[0018] The following is further described in detail through specific embodiments:

[0019] The reference signs in the drawings of the specification comprise a guardrail 1, a signal light 2, a controller 3, an alarm horn 4, a tunnel warning board 5, a communication module 6, a power supply module 7, an RSU unit 8, a vehicle-mounted OBU unit 9, a high-speed warning board 11, an indicator light 12, a lane 13 and a congested road section entrance 14.

[0020] The embodiment is basically as shown in the accompanying drawings. Figure 1 to the accompanying drawings. Figure 4

[0021] ​The edge computing-based road network perception system includes a cloud platform, response terminals, an edge computing controller 3, an industrial control computer, a communication module 6, a power supply module 7, an RSU unit 8, and an on-board unit 9. The edge computing controller 3 communicates with the cloud platform via the communication module 6. The edge computing controller 3 is connected to the industrial control computer, the power supply module 7, and the RSU unit 8. The RSU unit 8 can communicate with the on-board units 9 installed in vehicles on the road. The edge computing controller 3 collects vehicle data from the RSU unit 8 and processes the vehicle data. The vehicle data processing results are transmitted to the cloud platform and simultaneously to the industrial control computer. The industrial control computer controls the response terminals within its coverage area to perform actions according to the instructions of the edge computing controller 3.

[0022] The response terminal includes an alarm horn 4, a highway warning sign 11, a tunnel warning sign 5, and a traffic light 2, such as... Figures 2-4 As shown, municipal guardrails are installed along the length of both sides of lane 13. Warning traffic lights 2 are installed on the outer side of the guardrails 1, and an alarm horn 4 is installed on top of the traffic lights 2. Specifically, when congestion occurs, the industrial control computer controls the yellow and red lights of the traffic lights 2 to flash alternately, and the alarm horn 4 emits a voice announcement stating "Congestion ahead," to remind drivers of newly entering vehicles to pay attention to the road conditions ahead. In this embodiment, the coverage area of ​​the industrial control computer includes the tunnel section before the congested section. A tunnel warning sign 5 is suspended at the top of the tunnel exit, displaying information such as the specific direction of the congested section and the congestion time, such as "Congestion ahead in the XX direction, congestion time: 1 hour 50 minutes." Several indicator lights 12 are spaced upwards on the inner wall of the tunnel. The indicator lights 12 and the warning sign are all within the coverage area of ​​the industrial control computer and are electrically connected to it.

[0023] To further prevent the congestion on this one-way road from worsening, highway warning signs 11 will be installed at the intersections with other roads ahead of the congested section. Specifically, they can be installed at the entrance 14 of the congested section. The highway warning signs 11 can display congestion information and estimated travel time for all directions at the intersection, such as "Section XX ahead: Smooth traffic; Section XX ahead: Mild congestion; Section XX ahead: Severe congestion".

[0024] The utility model discloses a center end monitoring road network each road section's traffic condition, mainly used to collect and pretreat the data of the jammed road section, solve the problem that the owner of rear vehicle cannot obtain the road congestion condition in time through the equipment on the road network in time because of the close association of road traffic condition and APP software. Among them, data acquisition: OBU (the vehicle-mounted OBU unit 9 in this embodiment) is vehicle-mounted equipment, is used to connect the identification ETC card, usually pastes in the windshield of vehicle. RSU (RSU unit 8 in this embodiment) communicates with multiple OBU through the wireless communication mode of two-way microwave communication, receives the vehicle travel data from OBU. The existing RSU can obtain the congestion information of the current covered range through V2X technology, when RSU sends the congestion information to edge computing controller 3, edge computing controller 3 will send instructions to industrial computer to carry out higher level traffic management and control. Specifically, edge computing controller 3 can be connected with RSU through hardwiring or V2X communication protocol.

[0025] These data include the speed, position, driving direction, etc. of the vehicle, which are important basis for RSU to judge the traffic congestion situation.

[0026] The traffic condition (such as vehicle information) on the road includes embedded processor, embedded processor peripheral USB interface and RS485 interface etc., the embedded processor is ARM Cortex-A7 processor, and the main frequency of ARM Cortex-A7 processor is 528MHz;ARM Cortex-A7 processor has 256MB data storage space. Since the embedded processor ARM Cortex-A7 itself has smaller storage space, it is also connected with an extended memory, the memory is SD card, and the maximum capacity supports 32G, which fully meets the need of storing data. The communication module 6 is a GPRS module, a 3G / 4G / 5G module.

[0027] The specific implementation process is as follows:

[0028] The on-vehicle OBU unit 9 on different vehicles and the roadside RSU unit 8 arranged on the roadside collect road conditions, when the vehicle approaches the roadside RSU unit 8, the on-vehicle OBU unit 9 and the roadside RSU unit 8 are connected through dedicated short-range communication, the roadside RSU unit 8 collects all on-vehicle OBU units 9 in the passing range, compares the vehicle identity information ID of the OBU unit 8 and the RSSI value (signal strength) when communicating with each on-vehicle OBU unit 9, judges the congestion state according to the number of vehicles and the RSSI value change of each on-vehicle OBU unit 9, the method for judging road congestion is the prior art, the RSU unit 8 sends the congestion vehicle data to the edge computing controller 3, the edge computing controller 3 transmits to the cloud platform and the industrial computer in its coverage range after receiving, opens the signal lamp 2 of the crowded road through the industrial computer, and alerts the subsequent vehicles of the road through the alarm horn 4, the industrial computer also opens the tunnel warning sign and the high-speed warning sign 11 in front of the crowded road, and opens the indicator light 12 in the tunnel, reminding the subsequent vehicles to slow down, after the high-speed warning sign 11 in the front ramp of the vehicle crowded road displays information, it can help the driver to adjust the speed and the driving route in time.

[0029] The above is only an embodiment of the present application, and the common knowledge of specific structures and characteristics in the scheme is not described in detail. It should be pointed out that for those skilled in the art, without departing from the structure of the present application, a number of modifications and improvements can be made, which should also be considered as the protection scope of the present application, and these will not affect the effect and practicality of the present application. The protection scope of the present application should be subject to the content of its claims, and the specific implementation mode and the like in the specification can be used to explain the content of the claims.

Claims

1. A road network sensing system based on edge computing, characterized in that: The system includes a cloud platform, response terminals, an edge computing controller, an industrial control computer, a communication module, a power supply module, a Roadside Unit (RSU) and an On-Board Unit (OBU). The RSU is installed on the side of the congested road section, and the OBU is installed on each vehicle. The edge computing controller communicates with the cloud platform via the communication module. The edge computing controller collects vehicle data from the RSU and processes the data. The processed data is transmitted to the cloud platform and simultaneously to the industrial control computer. The industrial control computer controls the response terminals within its coverage area to perform actions according to the instructions of the edge computing controller. The response terminals are installed on the side of the congested road and / or on ramps, tunnels, or the side of the road ahead of the congested section.

2. The road network sensing system based on edge computing according to claim 1, characterized in that: The response terminal includes a highway warning sign, which is erected on the ramp leading to the congested road section. The highway warning sign can display information such as the direction of the congested section and the duration of the congestion.

3. The road network sensing system based on edge computing according to claim 2, characterized in that: The response terminal includes a tunnel warning sign and several indicator lights. The tunnel warning sign and indicator lights are installed inside the tunnel at the beginning of the congested road section. The tunnel warning sign can display information such as the direction of the congested section and the congestion time. The indicator lights are installed on the circumferential direction of the inner wall of the tunnel.

4. The road network sensing system based on edge computing according to claim 3, characterized in that: The response terminal includes an alarm horn and a traffic light. The traffic light is installed on the side of the congested road, and the alarm horn is installed on top of the traffic light. The alarm horn can emit a warning voice broadcast.

5. The road network sensing system based on edge computing according to claim 4, characterized in that: The edge computing controller includes an embedded processor, which is externally equipped with a USB interface and an RS485 interface.

6. The road network sensing system based on edge computing according to claim 5, characterized in that: The embedded processor is an ARM Cortex-A7 processor, and the embedded processor has external extended memory.

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